System Identification Based Methods for the Development of Nonlinear Dynamic Models for Flight Simulators

固定翼和旋翼训练模拟器是提高民用和军用航空安全的重要组成部分，CAE是世界上最大的训练模拟器供应商。可以说，训练模拟器最重要的部分是飞行模型，因为它驱动所有模拟器子系统。因此，民航监管机构要求飞行模型的行为在一套规定的公差范围内与真实飞机的行为相匹配。军用模拟器也有类似的要求。因此，经常通过选择模型的参数来开发飞行模型，使其行为与真实飞机记录的飞行测试数据相匹配。为测试飞机配备大量的仪器并进行大量的测试操作是非常耗时和昂贵的。此外，调整飞行模型的参数，使其行为与真实飞机相匹配，在所需的公差范围内，也是一个非常耗时的过程，需要昂贵的主题专家的大量参与。

Fixed wing and rotary wing training simulators are an important part of improving the safety of both civil and military aviation, and CAE is the world's largest supplier of training simulators. Arguably the most important part of a training simulator is the flight model as it drives all the simulator sub-systems. Therefore, the regulating bodies for civil aviation require the flight model behaviour to match that of the real aircraft within a specified set of tolerances. Military simulators have similar requirements. Flight models are therefore often developed by selecting the parameters of the model such that its behaviour matches recorded flight test data from the real aircraft. Outfitting the test aircraft with a vast array of instrumentation and flying a large set of test maneuvers is extremely time consuming and expensive. In addition, tuning the parameters of the flight model such that its behaviour matches the real aircraft, to within the required tolerances, is also extremely time-consuming process that requires significant involvement of expensive subject matter experts. This project aims to develop and apply new advanced system identification algorithms that will automatically estimate the parameters in a flight model such that its behaviour matches the recorded flight test data in an optimal sense. In addition, the same system identification algorithms will be used to determine the minimum airdata instrumentation requirements for the flight test aircraft that will result in a flight model with sufficient fidelity to comply with the appropriate regulations. Both of these tasks will greatly reduce CAE costs for developing training simulators, and potentially increase the fidelity of the simulators.